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Abstract

Background

Diagnosis and prognosis in breast cancer are mainly based on histology and immunohistochemistry
of formalin-fixed, paraffin-embedded (FFPE) material. Recently, gene expression analysis
was shown to elucidate the biological variance between tumors and molecular markers
were identified that led to new classification systems that provided better prognostic
and predictive parameters. Archived FFPE samples represent an ideal source of tissue
for translational research, as millions of tissue blocks exist from routine diagnostics
and from clinical studies. These should be exploited to provide clinicians with more
accurate prognostic and predictive information. Unfortunately, RNA derived from FFPE
material is partially degraded and chemically modified and reliable gene expression
measurement has only become successful after implementing novel and optimized procedures
for RNA isolation, demodification and detection.

Methods

In this study we used tissue cylinders as known from the construction of tissue microarrays.
RNA was isolated with a robust protocol recently developed for RNA derived from FFPE
material. Gene expression was measured by quantitative reverse transcription PCR.

Results

Sixteen tissue blocks from 7 patients diagnosed with multiple histological subtypes
of breast cancer were available for this study. After verification of appropriate
localization, sufficient RNA yield and quality, 30 tissue cores were available for
gene expression measurement on TaqMan® Low Density Arrays (16 invasive ductal carcinoma (IDC), 8 ductal carcinoma in situ
(DCIS) and 6 normal tissue), and 14 tissue cores were lost. Gene expression values
were used to calculate scores representing the proliferation status (PRO), the estrogen
receptor status and the HER2 status. The PRO scores measured from entire sections
were similar to PRO scores determined from IDC tissue cores. Scores determined from
normal tissue cores consistently revealed lower PRO scores than cores derived from
IDC or DCIS of the same block or from different blocks of the same patient.

Conclusion

We have developed optimized protocols for RNA isolation from histologically distinct
areas. RNA prepared from FFPE tissue cores is suitable for gene expression measurement
by quantitative PCR. Distinct molecular scores could be determined from different
cores of the same tumor specimen.

Background

Diagnosis and prognosis of breast cancer are still mainly based on clinical, histological
and immunohistochemical parameters, which are at best semi-quantitative [1,2]. Recently, molecular characterization of breast cancer has greatly increased the
understanding of biological pathways that are altered during neoplastic transformation.
Molecular markers have a great impact on elucidating the biological variance within
tumors, they allow new and more accurate classifications and they have the potential
to improve diagnosis, estimation of prognosis and treatment decisions in individual
patients [3-6].

Most gene expression studies are based on fresh frozen material which, in most instances,
is not readily available, as surgical samples are usually fixed in formalin. Unfortunately,
RNA derived from formalin-fixed, paraffin-embedded (FFPE) material is considerably
fragmented and chemically modified, often impairing gene expression measurement using
standard procedures. We developed a simple and robust protocol for RNA isolation and
partial de-modification from standard FFPE sections and documented that the isolated
RNA is suitable for gene expression measurement by quantitative reverse transcription
PCR (QRT-PCR) [7,8]. However, RNA isolated from tissue sections may not be representative for a tumor
as the proportion of normal tissue in a section may be significant. To circumvent
this problem, we used tissue cores as prepared for the construction of tissue microarrays
(TMA). TMAs allow to analyze hundreds of archival tissue samples simultaneously [9]. For a TMA, individual cores are punched from representative areas of a large series
of FFPE tissue blocks and re-assembled on a single recipient paraffin block. Sections
from TMA blocks are processed by staining, immunohistochemistry or in situ hybridization like regular tissue sections, revealing results from up to 1000 individual
tissue cores present on a single array [10,11].

We used such tissue cores as source of material for RNA isolation. In contrast to
sections which represent all tissue types present in the block, tissue cores have
the great advantage that they can be taken very precisely from the area of interest
within an individual tissue block [12,13]. In the present study, tissue cores were taken from normal and cancerous tissue of
the same block and gene expression was measured. We compared the level of expression
of various genes between invasive ductal carcinoma (IDC), ductal carcinoma in situ
(DCIS) and regions of histologically normal breast epithelium in single tissue blocks.

Methods

Tissue specimens and generation of tissue cores

Breast cancer specimens from 7 patients diagnosed with ductal carcinoma were retrieved
from the files of the Institute of Pathology, University of Bern. Tissue samples were
fixed with 4% neutralized formalin and embedded in paraffin. Sections from each of
a total of 16 tissue blocks (1 to 4 blocks per patient) were stained with hematoxylin
and eosin and regions containing IDC, DCIS and normal breast epithelium were marked
on each slide and the corresponding paraffin block (Fig. 1A and 1B). Three to 5 tissue cores were punched from each area of interest (1 to 5 areas in
each block) using a manual tissue microarrayer (Beecher Instruments, Sun Prairie,
WI, USA). In total, 3 to 5 tissue cores were taken from 44 individual areas. Cylinders
had a diameter of 0.6 mm and the length of the cores varied between 1 and 3 mm resulting
in approximately 0.3 to 1 mg tissue per core (Fig. 1E). After taking tissue cores, RNA was isolated from five 10 μm thick serial sections
that were collected from each tissue block at several levels separated by 400 μm.
Tissue was evaluated by hematoxylin and eosin staining of sections at each level and
the localization of tissue cores was verified microscopically within tumor and normal
tissue (Fig. 1C and 1D). Six tissue cores were excluded from further experiments because they did not represent
tissue from the appropriate area of interest. Histopathological characteristics of
each tumor, number of layers per block and number of areas punched and analyzed are
summarized in Table 1. All patients gave written informed consent to use their material. The study was
performed on the basis of an approval by the ethical committee of the Canton Bern,
Switzerland.

Figure 1.FFPE material before and after punching. Hematoxylin and eosin-stained tissue sections and paraffin block of patient 4 are
shown before and after punching tissue cores. Areas of IDC (red), DCIS (blue) and
normal tissue (green) were marked on the original tissue section (A) and on the corresponding
paraffin block (B). Tissue cores (E) were taken with a tissue microarrayer instrument.
Thereafter, sections were made from the remaining block and a control staining and
RNA isolation were done at ~400 μm intervals through the block (C and D). The area
containing DCIS was lost after ~400 μm and tissue cores contained fat instead of tumor
tissue. It was known from previous experiments that very little RNA can be isolated
from fat cells. Therefore, expression measurements in tissue cores containing fat
besides tumor tissue are not compromised.

RNA isolation and expression analysis

Entire tissue cores or 5 tissue sections were de-paraffinized with Neo-Clear (Merck,
Darmstadt, Germany), washed with ethanol and dried. RNA was isolated as described
previously [8] using the following modifications: 500 μl of lysis buffer containing approximately
1 μg/μl Proteinase K (Roche Diagnostics, Mannheim, Germany) was used. Tissue was homogenized
in a Mixer Mill at 20 Hz for 4 min and digested at 55°C for 1 hour. RNA was de-modified
and purified on silica-based columns as described previously [8]. RNA quantity and quality were assessed on a ND-1000 spectrophotometer (NanoDrop
Technologies, Wilmington, DE, USA) and on an Agilent 2100 Bioanalyzer (Agilent Technologies,
Inc., Santa Clara, CA, USA). Five tissue cores were excluded from subsequent experiments
due to insufficient RNA yield (less than 0.45 μg).

The quality of each RNA sample was further tested by QRT-PCR using TaqMan assays for
GUSB, RPLP0 and UBB (Applied Biosystems, Foster City, CA, USA) (Table 2) and a One-Step QRT-PCR protocol according to the recommendations of the manufacturer
(Invitrogen, Carlsbad, CA, USA). QRT-PCR was performed on an Applied Biosystems 7500
instrument in Fast mode (50°C for 15 min, 95°C for 2 min, followed by 45 cycles of
95°C for 3 sec and 60°C for 30 sec). Three RNA samples were excluded from further
analyses because the mean Ct value of the 3 control genes was considerably higher
than the mean of all other samples.

For the remaining 30 RNA samples gene expression levels were measured for control
genes and for genes associated with proliferation, estrogen receptor function and
HER2 using TaqMan® Low Density Arrays (TLDA; Applied Biosystems) on an Applied Biosystems 7900 HT instrument.
A list of assays used in this study is given in Table 2. Individual reactions were carried out with 2 ng of total RNA using the following
cycling conditions: 50°C for 15 min, 95°C for 2 min, followed by 40 cycles of 95°C
for 10 sec and 60°C for 30 sec.

Normalization of data

Raw data were recorded with the SDS software of the instruments. Delta cycle threshold
(Ct) values were determined as the difference between the Ct of each test gene and
the mean of RPLP0, UBB and GUSB (control genes). Scores representing the proliferation
status (PRO), the estrogen receptor status (ER) and the HER2 status (HER2) were computed
from 5 genes associated with proliferation (AURKA, MYBL2, CCNB1, MKI67 and BIRC5),
4 genes related to estrogen receptor function (ESR1, PGR, BCL2 and SCUBE2) and 2 genes
related to HER2 (ERBB2 and GRB7). The procedure for calculating scores was described
previously [8].

Total RNA was isolated from tissue cores and from sections as described in Methods
and according to the previously established protocol [8]. RNA yield was assessed spectrophotometrically (Fig. 2A). For a better comparison of recoveries from individual samples, the RNA yield was
converted to numbers corresponding to 3 tissue cores with an average length of 3 mm
or to 1 tissue section (10 μm thick), respectively. The mean recovery from tissue
cores was 4.0 μg (range 0.3 – 8.5) for IDC, 2.3 μg (0.8 – 6.2) for DCIS and 0.8 μg
(0.2 – 2.2) for normal tissue. The corresponding mean yield per tissue section was
2.3 μg (range 0.3 – 6.3). The quality of each RNA was tested on a Bioanalyzer (Fig.
2B) and by measuring gene expression of 3 control genes (GUSB, RPLP0 and UBB) by QRT-PCR
(Fig. 2C). Bioanalyzer results revealed fragment lengths between 100 and 2000 bp with mean
fragment lengths around 500 bp which is typical for good quality RNA from FFPE material.
The mean of all 3 control genes was Ct = 24.3 (range 23.8 – 25.2) for IDC, Ct = 24.8
(23.6 – 28.5) for DCIS and Ct = 26.0 (23.9 – 30.3) for normal tissue cores. Corresponding
mean expression for tissue sections revealed Ct = 25.1 (range 23.4 – 26.3).

Figure 2.Characterization of RNA. RNA was isolated from tissue cores and from histological sections and RNA concentration
was measured spectrophotometrically (A). RNA yield was converted to correspond to
3 tissue cores with an average length of 3 mm or to 1 tissue section (10 μm thick),
respectively. Mean recoveries and corresponding standard deviations are shown for
17 IDC, 9 DCIS and 12 normal tissue cores (N) and for 40 tissue sections (S). Five
RNAs were excluded from subsequent experiments because RNA yield was less than 0.45
μg. The quality of each RNA sample was tested on a Bioanalyzer. A representative,
gel-like picture for each histological type is shown (B). RNA quality was further
assessed by QRT-PCR and mean Cts of 3 control genes (GUSB, RPLP0 and UBB) are shown
(C). One RNA sample from DCIS and 2 RNA samples from normal tissue were excluded from
subsequent expression measurement because mean Ct values of control genes were more
than one standard deviation higher than the mean of all Cts (arrows).

Gene expression levels were measured on TLDAs. Gene expression of each test gene was
normalized using the mean of RPLP0, GUSB and UBB as reference. Putative control genes
were previously compared by QRT-PCR with RNA of more than 80 matched samples of fresh
frozen and archival FFPE material, which revealed that GUSB, RPLP0 and UBB are the
3 most stably expressed genes in breast cancer that can be measured reliably by QRT-PCR
(Antonov et al., manuscript in preparation). Scores were computed from genes related
to PRO, ER and HER2 status as described in Methods. Fig. 3 shows PRO scores computed from tissue cores (symbols below dashed lines) and from
sections (symbols above dashed lines) for all 7 patients. Tissue cores and sections
derived from the same block are shown in the same color. Tissue cores from IDC, DCIS
and normal tissue are represented as circles, diamonds and triangles, respectively.
Sections representing a mixture of more than one tumor type are depicted as squares.
Replicate cores taken from histologically homogeneous tissue regions gave similar
scores (tissue cores from patients 1–5) corroborating that the procedure for determining
PRO scores is robust. Similar scores were also measured between tissue cores and sections
in cases where blocks contained only one type of tumor or normal tissue (for example
patient 6).

Figure 3.PRO scores from tissue cores and from sections. PRO scores were computed from tissue cores (symbols below dashed lines) and from
sections taken at different levels of tissue blocks (symbols above dashed lines).
Scores derived from IDC are represented by circles, DCIS by diamonds and normal tissue
by triangles. Sections containing IDC, DCIS and/or normal tissue are shown as squares,
sections containing only one tissue type are given with the same symbols as tissue
cores. Cores and sections derived from the same tissue block are shown in the same
color.

Blocks from several patients contained IDC, DCIS and normal tissue in the same paraffin
block (patients 1, 2 and 4). In all these cases, the PRO scores measured from entire
sections were similar to PRO scores determined from IDC tissue cores. This is most
likely due to a higher RNA content in tumor cells than in normal breast tissue. Scores
determined from normal tissue cores consistently revealed low PRO scores while PRO
scores were higher for IDC or DCIS of the same block or from different blocks of the
same patient (patients 1–6). Samples from patient 7 contained IDC which had a relatively
low PRO score corresponding to cancers which have a more favorable prognosis than
cancers which have high PRO scores (Antonov et al., manuscript in preparation). In
all patients PRO scores were fairly similar for DCIS and IDC. A similar observation
was reported previously by others [14,15] who compared atypical ductal hyperplasia, DCIS and IDC and showed high degrees of
similarity at the level of gene expression between these pathological stages. Both
studies were based on fresh frozen material.

Tissue cores used in this study had a length of about 3 mm. To investigate whether
the tissue was histologically homogenous in the vertical dimension, 3 mm of each block
were sectioned and every 400 μm one section was stained and 5 sections were taken
for RNA isolation. In most cases morphology was similar at different levels (Fig.
1A, C and 1D). Similarly, RNA derived from each layer gave similar PRO scores (Fig. 3, blocks from patients 1 – 5, upper rows). This is in agreement with other studies,
which showed by TMA and immunohistochemistry that data generated from tissue cores
yield clinically significant and representative results [16,17]. The PRO score which is generated from proliferation-related genes was also compared
to Ki-67 labeling index which was determined by immunohistochemistry from sections.
The PRO scores determined from tissue cores of IDC and DCIS or from tissue sections
in the 7 patients are in good agreement with Ki-67 labeling index (Table 1 and Fig. 3). Tissue cores were also evaluated with respect to ER and HER2 scores confirming
that RNA from tissue cores is suitable for gene expression measurement (data not shown).

Conclusion

The method presented here is suitable for FFPE tissue, it can be combined with traditional
TMA studies without great additional effort allowing to match molecular markers with
morphological, immunohistochemical and/or in situ analyses. Comparing stained tissue sections before and after taking tissue cores allows
to control very precisely whether material was taken from the expected area and cores
representing unwanted tissue regions can be excluded from further analysis. Sufficient
RNA can be isolated from 3 to 5 tissue cores for multiple QRT-PCR analyses (at least
100 reactions) without the need for RNA amplification.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

MS and RJ organized the study, planned the experiments and wrote the manuscript. AO
and MS carried out RNA isolations, quality controls and gene expression measurements.
AB was responsible for preparation of tissue cores, sections and stainings. HB and
MG selected the samples and carried out the histopathological assessment. AK was responsible
for histology and diagnostic stainings. All authors read and approved the final manuscript.

Acknowledgements

The authors wish to thank Dr. S. Aebi and J. Antonov for helpful discussions and critical
reading of the manuscript. This work was supported by the Swiss Cancer League (Grant
OCS-02132-08-2007 to RJ) and the Novartis Foundation for Biomedical Research (to RJ).
Material was provided by the Institute of Pathology, University of Bern and the Tumorbank
Bern. The Tumorbank Bern is sponsored by the Department of Clinical Research, the
Institute of Pathology of the University of Bern and the Bernese Cancer League.